JP6954358B2 - Fine particle measuring device, information processing device and information processing method - Google Patents

Description

The present technology relates to a fine particle measuring device, an information processing device, and an information processing method, and more particularly to a technique of a fine particle measuring device that optically measures the characteristics of fine particles such as cells.

In general, flow cytometry (flow cytometer) is widely used for analyzing proteins of biologically related fine particles such as cells, microorganisms and liposomes. Flow cytometry irradiates fine particles that flow in a row in a flow path with laser light (excitation light) of a specific wavelength, and detects fluorescence and scattered light emitted from each fine particle. , This is a method of analyzing a plurality of fine particles one by one. In this flow cytometry, the type, size, structure, etc. of individual fine particles can be determined by converting the light detected by the photodetector into an electrical signal, quantifying it, and performing statistical analysis.

In the fields of basic medicine and clinical practice, multicolor analysis using a plurality of fluorescent dyes has become widespread in flow cytometry in order to promote comprehensive interpretation. However, when a plurality of fluorescent dyes are used in one measurement as in multicolor analysis, light from a fluorescent dye other than the intended one leaks into each detector, and the analysis accuracy is lowered. Therefore, in the conventional flow cytometer, fluorescence correction is performed in order to extract only the target optical information from the target fluorescent dye. However, in the case of fluorescent dyes having close spectra, an event occurs in which fluorescence correction cannot be performed because the leakage to the detector becomes large.

Here, for fluorescence detection in the flow cytometer, in addition to the method of selecting a plurality of light in a discontinuous wavelength range using a wavelength selection element such as a filter and measuring the intensity of the light in each wavelength range, the method is continuous. There is also a method of measuring the intensity of light in the wavelength range as a fluorescence spectrum. For example, Patent Document 1 discloses a spectrum type flow cytometer capable of measuring a fluorescence spectrum, which disperses fluorescence emitted from fine particles using a spectroscopic element such as a prism or a grating. The spectral flow cytometer is a system that analyzes the amount of fluorescence of each fine particle by deconvolving the fluorescence data measured from the fine particles with the spectral information of the fluorescent dye used for staining.

As an example, the spectral type flow cytometer of Patent Document 1 detects the dispersed fluorescence by using a light receiving element array in which a plurality of light receiving elements having different detection wavelength ranges are arranged. Further, in the light receiving element array, a plurality of independent detection channels such as a PMT array or photodiode array in which light receiving elements such as PMT or photodiode are arranged in one dimension, or a two-dimensional light receiving element such as CCD or CMOS are arranged. The thing is used.

Japanese Unexamined Patent Publication No. 2013-61244

However, the technique proposed in Patent Document 1 may not be able to further improve the spectrum separation performance.

Therefore, this technique has been made in view of such a situation, and its main purpose is to provide a fine particle measuring apparatus having reduced noise and improved spectral separation performance.

In this technology, a detector having a plurality of detectors for detecting light from fine particles, a magnification setting unit for setting a magnification for each of the plurality of detectors, and a correction coefficient based on the set magnification are set. Provided is a spectrum type fine particle measuring device including a correction coefficient calculation unit for calculation and a spectrum generation unit for correcting a value detected by a detector with a calculated correction coefficient to generate spectrum data.

In addition, the present technology includes a magnification setting unit that sets the magnification for each of a plurality of detectors that detect light from fine particles, a correction coefficient calculation unit that calculates a correction coefficient based on the set magnification, and a correction coefficient calculation unit. Provided is an information processing apparatus including a spectrum generation unit that generates spectrum data by correcting a value detected by a detector with a calculated correction coefficient. Further, in the present technology, the processor sets a multiplication factor for each of a plurality of detectors that detect light from fine particles, a step of calculating a correction coefficient based on the set multiplication factor, and a detector. Provided is an information processing method including a step of correcting a detected value with a calculated correction coefficient to generate spectral data.

According to the present technology, it is possible to provide a fine particle measuring apparatus having reduced noise and improved spectral separation performance. The effects described here are not necessarily limited, and may be any of the effects described in the present disclosure, or an effect different from them.

It is the schematic which shows the structural example of the fine particle measuring apparatus which concerns on this technique. It is a block diagram which shows the structural example of the fine particle measuring apparatus of 1st Embodiment which concerns on this technique. It is a block diagram which shows the structural example of the data analysis part of the 1st Embodiment which concerns on this technique. It is a flowchart which shows an example of the processing operation of the fine particle measuring apparatus of 1st Embodiment which concerns on this technique. It is a graph which shows the spectrum chart of the excitation when the single-stained particles of a fluorescent dye obtained by the measurement using the microparticle measuring apparatus of 1st Embodiment which concerns on this technique are mixed. It is a graph which shows the spectrum chart of each excitation of the single-stained particle for each fluorescent dye obtained by the measurement using the microparticle measuring apparatus of 1st Embodiment which concerns on this technique. It is a graph which shows the selected effective data in the condition setting sample obtained by the measurement using the microparticle measuring apparatus of 1st Embodiment which concerns on this technique. It is a graph which shows the individual gain setting value and the value of the correction coefficient of PMT obtained from the data of 5 fluorescent dyes of 1st Embodiment which concerns on this technique. It is a figure which shows the state which gain-adjusted each channel of PMT individually to the upper limit value with respect to the selected valid data of 1st Embodiment which concerns on this technique. It is a figure explaining the calculation process of the correction coefficient with respect to the data including the data of 5 fluorescent dyes using the microparticle measuring apparatus of 1st Embodiment which concerns on this technique. It is a graph which shows the reference spectrum calculated by using the microparticle measuring apparatus of 1st Embodiment which concerns on this technique. It is a calculation formula of the general least squares method (LSM) and the weighted least squares method (WLSM) for unmixing that performs fluorescence separation of multiple staining samples using a reference spectrum. It is a graph which shows an example of the characteristic curve of 1st Embodiment which concerns on this technique. It is a figure explaining the calibration using the sample which mixed a plurality of fine particles of 1st Embodiment which concerns on this technique. It is a figure which shows the measurement of 8 peak beads which mixed fine particles whose fluorescence intensity was adjusted in 8 steps for sensitivity evaluation of 1st Embodiment which concerns on this technique. It is a figure which shows the spectral shape which cut out the data for every fluorescence wavelength band of the typical fluorescent dye of 1st Embodiment which concerns on this technique. It is a graph which shows an example of the plot of the separation performance of 8 peaks for each fluorescence wavelength band of the fluorescent dye of 1st Embodiment which concerns on this technique. It is a graph which shows an example of the plot of the separation performance of 8 peaks for each fluorescence wavelength band of the fluorescent dye of 1st Embodiment which concerns on this technique. It is a block diagram which shows the hardware configuration example of the information processing apparatus which concerns on this technology.

Hereinafter, suitable embodiments for carrying out the present technology will be described with reference to the drawings. The embodiments described below can be combined with any of the embodiments. It shows an example of a typical embodiment of the present technology, and the scope of the present technology is not narrowly interpreted by this. In addition, the embodiments described below may be a combination of any one or more embodiments. In the drawings, the same or equivalent elements or members are designated by the same reference numerals, and duplicate description will be omitted.

The explanation will be given in the following order.
1. 1. Outline of fine particle measuring device 2. First Embodiment (Structure example of a fine particle measuring device)
(2-1) Configuration example of the fine particle measuring device (2-2) Configuration example of the data analysis unit (2-3) Operation example of the fine particle measuring device (2-4) Example 3. Hardware configuration example

<1. Overview of fine particle measuring device>
An outline of the fine particle measuring apparatus according to the present technology will be described with reference to FIG. In this embodiment, a spectral flow cytometer will be used as an example of the fine particle measuring device.

FIG. 1 is a schematic view showing a configuration example of a fine particle measuring device according to the present technology. As shown in FIG. 1, the spectral type flow cytometer 1 which is a fine particle measuring device includes, as an example, a laser light source 11, a lens 12, a fluid optical system 13, a filter detector 14, and a user interface 15. Further, the spectrum type flow cytometer 1 includes a prism 16 and an array type high sensitivity detector (PMT) 17 for detecting a spectrum. In this embodiment, PMT17 is used as the photodetector, but the detector is not limited to this, and may be an APD or the like.

The spectral type flow cytometer 1 irradiates fine particles such as cells and beads passing through the flow cell with light from the laser light source 11, and detects fluorescence and scattered light emitted from the fine particles to detect each fine particle. It is a fine particle measuring device that optically measures the characteristics of the above. Further, the fluid optical system 13 is a system that analyzes and sorts fine particles by detecting optical information obtained from fine particles arranged in a row in a flow cell (flow path).

For example, when detecting the fluorescence of a cell, the cell labeled with a fluorescent dye is irradiated with excitation light having an appropriate wavelength and intensity such as laser light. Then, the fluorescence emitted from the fluorescent dye is focused by a lens 12 or the like, light in an appropriate wavelength band is selected using a wavelength selection element such as a filter of the filter detector 14 or a dichroic mirror, and the selected light is PMT. (Photo multiplier tube) Detection is performed using a light receiving element such as 17. At this time, by combining a plurality of wavelength selection elements and a plurality of light receiving elements, it is possible to simultaneously detect and analyze fluorescence from a plurality of fluorescent dyes labeled on cells. Furthermore, the number of fluorescent dyes that can be analyzed can be increased by combining excitation lights of a plurality of wavelengths.

Generally, for fluorescence detection in a flow cytometer, in addition to a method of selecting a plurality of light in discontinuous wavelength bands using a wavelength selection element such as a filter and measuring the intensity of light in each wavelength band, continuous wavelengths are used. There is a method of measuring the intensity of light in the band as a fluorescence spectrum. In the spectrum type flow cytometer 1 capable of measuring the fluorescence spectrum, the fluorescence emitted from the fine particles is separated by using a spectroscopic element such as a prism 16 or a grating. Then, the spectroscopic fluorescence is detected by using the light receiving element array 17 in which a plurality of light receiving elements having different detection wavelength bands are arranged. As the light receiving element array 17, a PMT array in which PMT light receiving elements are arranged one-dimensionally is used. As the light receiving element array, a photodiode array in which light receiving elements such as photodiodes are arranged one-dimensionally, or one in which a plurality of independent detection channels such as two-dimensional light receiving elements such as CCD or CMOS are arranged may be used. can.

In the analysis of fine particles represented by flow cytometry, an optical method is often used in which the fine particles to be analyzed are irradiated with light such as a laser to detect fluorescence or scattered light emitted from the fine particles. .. As an example, based on the optical information detected by the spectral type flow cytometer 1, a histogram is extracted by an analysis computer and software, and analysis is performed.

In the optical analysis of fine particles, quality control (QC: Quality Control) is performed to verify the accuracy of the fine particles to be inspected and to confirm and standardize the operation of the device before the optical measurement of the fine particles to be inspected. ) May be performed. In this quality control, a plurality of beads (3-peak beads, 6-peak beads, 8-peak beads, etc.) labeled with fluorescent dyes having different fluorescence intensities or one type of beads (align check) that can obtain a wide spectrum are usually obtained. Beads, Ultra Rainbow fluorescent particles, etc.) are used.

A normal spectrum type flow cytometer is provided with an array type high sensitivity detector for detecting a spectrum, instead of the high sensitivity detector in which a large number of conventional flow cytometers are arranged. Compared to the conventional type, it is not configured to have one high-sensitivity detector for one fluorescent dye, so it is difficult to set the target value of the detection sensitivity, and the array type detector has a large number of PMTs, so the user can use it. It is very difficult to manually set an appropriate magnification for each PMT. In addition, there are many parameters to be considered that affect the result when calculating the amount of fluorescence by deconvolution processing based on spectral information. Most of the devices currently realized are configured so that they can be easily operated by limiting the degree of freedom of parameters to a range that can be controlled by a general user. Therefore, there is a situation in which the separation ability of the fluorescent dye, which is originally possessed by the spectral flow cytometer, cannot be maximized. The present technology aims to solve such a problem.

<2. First Embodiment (Structure example of a fine particle measuring device)>
(2-1) Configuration Example of Microparticle Measuring Device FIG. 2 is a block diagram showing a configuration example of the microparticle measuring apparatus of the first embodiment according to the present technology. A configuration example of the fine particle measuring device according to the present embodiment will be described with reference to FIGS. 1 and 2.

As shown in FIG. 2, the spectrum type flow cytometer 1 which is a fine particle measuring device includes a fluorescence spectrum detecting unit 21 and an information processing device 22. In the spectrum type flow cytometer 1, the laser light source 11, the lens 12, the fluid optical system 13, and the filter detector 14 shown in FIG. 1 serve as the fluorescence spectrum detection unit 21, and the user interface 15 is the information processing device 22. Has the role of. The information processing device 22 includes a device control unit 23, a data recording unit 24, and a data analysis unit 25.

The fluorescence spectrum detection unit 21 is a portion that detects the amount of fluorescence of a large number of fine particles. When the fluorescence spectrum detection unit 21 optically analyzes the fine particles, first, the excitation light is emitted from the light source of the laser light source 11 and irradiates the fine particles flowing in the flow path of the fluid optical system 13. Next, the fluorescence emitted from the fine particles is detected by the filter detector 14. Specifically, a dichroic mirror, a bandpass filter, or the like is used to separate only light of a specific wavelength (target fluorescence) from the light emitted from fine particles, and this is separated into a detector such as a 32-channel PMT17. Detect with. At this time, for example, a prism 16 or a diffraction grating is used to disperse the fluorescence so that light having a different wavelength is detected in each channel of the detector. Thereby, the spectral information of the detected light (fluorescence) can be easily obtained. The fine particles to be analyzed are not particularly limited, and examples thereof include cells and microbeads.

The device control unit 23 is a part that sets conditions for measuring fine particles and controls the operation of the device. More specifically, the device control unit 23 optimizes by changing parameters such as liquid feeding conditions of a sample containing fine particles, output of a laser light source 11 related to fluorescence detection, sensitivity control of a fluorescence detector, and position adjustment of an optical stage. This is the part to be converted. As a specific work procedure of the device control unit 23, in order for the user to set the optimum conditions for obtaining the desired result for the sample to be measured, the actual sample is sent and the detected fluorescence signal is used. While watching, repeat the work of adjusting various parameters as needed. The device control unit 23 is configured so that the user can change the parameters of the device mainly from the control software by the computer so that the setting can be easily changed.

The data recording unit 24 is a unit that records the spectrum data of each fine particle detected by the fluorescence spectrum detection unit 21. The data recording unit 24 has a function of recording the spectrum information of each fine particle acquired by the fluorescence spectrum detection unit 21 together with scattered light other than the spectrum information and information on time and position. The recording function of the data recording unit 24 mainly uses a computer memory or an optical disc. In normal cell analysis, thousands to millions of fine particles are analyzed under one experimental condition, so that the data recording unit 24 records a large amount of spectral information in a state organized according to the experimental condition. It is necessary.

The data analysis unit 25 is a unit that performs various data processing so that a desired analysis result can be obtained from the data recorded in the data recording unit 24. The data analysis unit 25 quantifies the light intensity of each wavelength band detected by the fluorescence spectrum detection unit 21 using a computer or the like, and obtains and analyzes the fluorescence amount (light intensity) for each fluorescent dye used. For this analysis, linear fitting by the least squares method using a reference spectrum calculated from experimental data is used.

The reference spectrum is calculated by statistical processing using two types of measurement data of fine particles stained with only one fluorescent dye and measurement data of unstained fine particles. By properly performing this statistical processing, the reference spectrum shape of the fluorescent dye used for plausible staining and the reference spectrum shape of autofluorescence of unstained fine particles can be estimated from the actual data measured by the spectrum cytometer. It is necessary.

Further, the calculated reference spectrum is recorded in the data recording unit 24 together with information such as the name of the fluorescent molecule, the measurement date, and the type of fine particles. The fluorescence amount (fluorescence spectrum data) of the sample estimated by the data analysis unit 25 is stored in the data recording unit 24, displayed in a graph according to the purpose, and the fluorescence amount distribution of the fine particles is analyzed. The main part of the present technology is an algorithm that calculates the setting parameters used by the device control unit 23 from the data measured by the data analysis unit 25 and reflects them up to the fluorescence separation processing calculation.

(2-2) Configuration Example of Data Analysis Unit Next, a configuration example of the data analysis unit 25 of the present embodiment will be described. FIG. 3 is a block diagram showing a configuration example of the data analysis unit 25 of the present embodiment. The data analysis unit 25 includes a magnification setting unit 31, a correction coefficient calculation unit 32, a spectrum generation unit 33, a data adjustment unit 34, a reference spectrum calculation unit 35, a spectrum separation unit 36, and a detector evaluation unit 37. And have.

The magnification setting unit 31 sets the magnification for each PMT 17 which is a plurality of detectors for detecting light from fine particles, which is possessed by the fluorescence spectrum detection unit 21. The magnification setting unit 31 can set the magnification based on the applied voltage of the detector. Further, the magnification setting unit 31 automatically sets the magnification from one measurement data of a sample mixed with a single-staining sample stained with one fluorescent dye or a multi-staining sample stained with all the fluorescent dyes. be able to.

The correction coefficient calculation unit 32 calculates the correction coefficient based on the magnification set by the magnification setting unit 31. The correction coefficient calculation unit 32 can automatically calculate the correction coefficient from one measurement data of a sample mixed with a single-staining sample stained with one fluorescent dye or a multi-staining sample stained with all the fluorescent dyes. can. Further, the correction coefficient can be calculated from the applied voltage individually set for each PMT 17. This correction coefficient is, for example, a value based on the uniformity of the detector, the width of the wavelength band detected for each of the plurality of detectors, or the wavelength dependence of the photoelectric conversion. Further, the correction coefficient may be calculated from the actual data by measuring the condition setting sample after adjusting the individual gain.

The spectrum generation unit 33 corrects the value detected by the PMT 17 which is a detector with the correction coefficient calculated by the correction coefficient calculation unit 32 to generate spectrum data.

The data adjustment unit 34 automatically adjusts the maximum value of the value detected by the fluorescence spectrum detection unit 21 to a predetermined threshold value based on the magnification set by the magnification setting unit 31. By obtaining the relational expression between the multiplication factor and the applied voltage for all the individual PMT17s in advance, the data adjusting unit 34 uses the relational expression to multiply the applied voltage by several times to set the maximum value as a threshold value. Can be automatically calculated and adjusted to reach. The predetermined threshold value can be the detection upper limit value of the PMT17 which is a detector.

The reference spectrum calculation unit 35 calculates a reference spectrum based on the spectrum data generated by the spectrum generation unit 33. The calculated reference spectrum data is either spectrum data obtained by previously measuring fine particles containing a known fluorescent substance with a spectral flow cytometer 1 and corrected by the above-mentioned correction coefficient, or the fluorescence spectrum of the fluorescent substance. It may be any of the spectral data obtained by measuring with a normal fluorescence spectrophotometer.

The spectrum separation unit 36 separates using the reference spectrum calculated by the reference spectrum calculation unit 35. The spectrum separation unit 36 can perform the spectrum separation process based on the calculated correction coefficient by using the weighted least squares method described later.

The detector evaluation unit 37 evaluates each PMT 17 which is a detector using measurement data obtained by mixing a plurality of fine particles having different fluorescence intensities and particle sizes. The detector evaluation unit 37 can obtain the relational expression between the multiplication factor and the applied voltage by using an evaluation jig or the like in the inspection when manufacturing the spectral type flow cytometer 1. As a result, even if the spectral type flow cytometer 1 changes with time, the relational expression between the magnification and the applied voltage can be updated by a simple measurement.

(2-3) Example of processing operation of the fine particle measuring device FIG. 4 is a flowchart showing an example of the processing operation of the fine particle measuring device of the present embodiment. An example of the processing operation of the spectral flow cytometer 1 which is the fine particle measuring apparatus of the present embodiment will be described with reference to FIG. A detailed operation example in each step will be described later, but first, the flow of the entire measurement algorithm will be described.

In step S401, first, the sample fine particles for setting the conditions are prepared, and the device control unit 23 sets the conditions for measuring the sample fine particles. When the measurement conditions are set, the fluorescence spectrum detection unit 21 measures the fine particles of the sample under the set constant conditions. At that time, the data adjusting unit 34 automatically adjusts the entire PMT value so that the fluorescence values of all the fine particles do not exceed the limit of PMT17. Here, how to adjust the overall PMT value will be described. First, when the upper limit value is simply measured, the PMT applied voltage is lowered for measurement, and when the upper limit value is detected again, the PMT applied voltage is repeatedly lowered. Then, this is automatically repeated until the measured value becomes equal to or less than the upper limit value, and the total PMT value is adjusted. If the measured value exceeds the upper limit value, since the true value is unknown, it is unclear how much the intensity should be adjusted, so a trial and error is required. After adjusting the PMT value, the fluorescence spectrum detection unit 21 measures sample data of a certain number of fine particles, and the data recording unit 24 records and stores the measured sample data.

In step S402, the display unit of the user interface 15 displays the sample data measured in step S401 as a graph. From the displayed graph, the user sets the range of the fine particles to be analyzed and selects valid data.

In step S403, the magnification setting unit 31 calculates a meaningful maximum value in all PMT17 channels in the valid data group selected in step S402. The magnification setting unit 31 calculates the ratio between the calculated maximum value and the measurement upper limit value, obtains a value for adjusting the maximum value of each PMT17 channel to the vicinity of the measurement limit value, and increases the magnification of each PMT17 channel. Set (gain) individually. Further, the correction coefficient calculation unit 32 calculates a correction coefficient for returning the reciprocal of the gain value obtained for multiplying the detected value to the original waveform.

In step S404, first, the device control unit 23 sets the gain of each PMT 17 individually. When the gain of each PMT 17 is set individually, the fluorescence spectrum detection unit 21 executes a sample measurement for actually performing the analysis. The data recording unit 24 records and stores the sample measurement data.

In step S405, the spectrum generation unit 33 calculates by multiplying all the data measured in step S404 by a correction coefficient for each channel, and reproduces the general fluorescence spectrum shape lost by the individual gain setting. Generates spectral data.

In step S406, the reference spectrum calculation unit 35 calculates and creates a reference spectrum for each fluorescent dye required for analysis of the spectral flow cytometer 1 from the data of the single-stained sample generated by correction in step S405. do. Further, the spectrum separation unit 36 also performs fluorescence separation (Unmixing treatment) on the corrected multi-staining sample by using the weighted least squares method (WLSM) in step S406. In this Unmixing process, when the weighted least squares method is used, it is possible to optimize for fixed noise by reflecting the value of the correction coefficient in the weight parameter, and it is possible to realize more accurate fluorescence separation process.

(2-4) Example A detailed operation example in each step of the processing operation of the spectral type flow cytometer 1 of the present embodiment will be described with reference to the examples shown in FIGS. 5 to 18.

[Measurement example of sample for setting conditions (S401)]
FIG. 5 is a graph showing a spectrum chart of 488 nm excitation when single-stained particles of five fluorescent dyes obtained by measurement using a spectral flow cytometer 1 are mixed. FIG. 5A shows an excitation spectrum chart before the automatic gain adjustment of each PMT17, and FIG. 5B shows an excitation spectrum chart after the automatic gain adjustment of each PMT17. The horizontal axis of FIG. 5 represents the channel of PMT17, and the vertical axis represents the fluorescence signal intensity.

FIG. 6 is a graph showing a spectrum chart of 488 nm excitation of single-stained particles for each of the five fluorescent dyes obtained by measurement using a spectral flow cytometer 1. FIG. 6A shows an excitation spectrum chart for each dye before the gain of each PMT17 is automatically adjusted, and FIG. 6B shows an excitation spectrum chart for each dye after the gain of each PMT17 is automatically adjusted. The horizontal axis of FIG. 6 represents the channel of PMT17, and the vertical axis represents the fluorescence signal intensity.

In step S401 for measuring the condition setting sample, for example, a multi-staining sample stained with all the fluorescent dyes used in the measurement or a mixture of all the single-staining samples is used. As shown in FIG. 5A, a certain number of data are measured while sending this sample to a flow cytometer. After that, the PMT channel indicating the maximum value in the measured data and the maximum value are obtained. Then, as shown in FIG. 5B, the gains of all the array type PMTs are uniformly and automatically adjusted so that the maximum value becomes the detection upper limit value.

Further, in the normal array type PMT, when the gain is uniformly increased or decreased, the measured value is also uniformly increased or decreased at the same rate. Therefore, as shown in FIGS. 6A and 6B, even when a plurality of excitation lasers and an array type PMT17 are provided, by increasing or decreasing each PMT17 uniformly, there is a slight influence of individual differences in PMT17. The spectral shape of the fluorescent dye can be measured with almost no change. The condition setting sample is measured while maintaining the shape of this fluorescence spectrum and setting the PMT gain to the optimum setting.

[Example of selecting valid data (S402)]
FIG. 7 is a graph showing the selected valid data in the condition setting sample obtained by the measurement using the spectral type flow cytometer 1. FIG. 7A is a histogram showing the cell number frequency distribution of the gated microparticles by selecting (gating) only the cell population of interest in the measured sample. The horizontal axis of FIG. 7A represents the integrated value of the lateral scattering intensity, and the vertical axis represents the maximum value of the lateral scattering intensity. FIG. 7B shows an excitation spectrum chart of each PMT17 before the automatic adjustment of the gain, and FIG. 7C shows an excitation spectrum chart of each PMT17 after the automatic adjustment of the gain. The horizontal axis of FIGS. 7B and 7C represents the wavelength of PMT17, and the vertical axis represents the fluorescence signal intensity.

In step S402 for selecting valid data, the measurement result of the condition setting sample is displayed as a graph on the display unit of the user interface 15 so that the user can set the data range to be analyzed. In the measurement of the spectral type flow cytometer 1, a biological sample such as a cell is often used, and various impurities are contained. This measurement may cover a very small number of particles, such as one in one million, and there are various requirements for each user, so it is difficult to automatically select valid data. be. Therefore, when selecting valid data that serves as a reference for adjusting the individual gain of the PMT 17, the user sets the gate of the effective range while looking at the displayed graph, extracts the data group from which impurities and the like have been removed, and obtains the individual gain of the PMT 17. Select valid data to be the basis for adjustment.

[Example of PMT individual gain setting and correction coefficient calculation (S403)]
FIG. 8 is a graph showing individual gain setting values and correction coefficient values of PMT17 obtained from the data of the five fluorescent dyes of the spectral flow cytometer 1. FIG. 8A is a diagram showing the maximum value and the detection upper limit value of each channel of PMT17 with respect to the valid data selected and set. The horizontal axis of FIG. 8A represents the wavelength, and the vertical axis represents the fluorescence signal intensity. FIG. 8B shows the multiplication factor (gain) of each PMT17 obtained from the data of the five fluorescent dyes, and FIG. 8C shows the correction coefficient of each PMT17 obtained from the data of the five fluorescent dyes. The horizontal axis of FIGS. 8B and 8C represents the channel of PMT17, and the vertical axis represents the multiplication factor and the correction coefficient, respectively.

In step S403 of setting the individual gain of the PMT and calculating the correction coefficient, the maximum value of each channel of the PMT 17 is calculated with respect to the set valid data. Then, it is estimated from the difference from the detection upper limit value how many times the data can be increased without saturation, and the individual gain value of each channel of the PMT 17 is calculated. In order to avoid the expansion of unnecessary noise components in this calculation, the upper limit of the gain may be set in the region where the signal is very small due to the configuration of the optical filter and the excitation laser. FIG. 8B shows the magnification of each PMT17 obtained from the data of the five fluorescent dyes, and an upper limit of about 30 times is set from the reference measurement result. Further, FIG. 8C shows a value of the reciprocal of the multiplication factor, and this value is a correction coefficient required for spectrum reproduction.

[Sample measurement example (S404)]
FIG. 9 is a diagram showing a state in which each channel of the PMT 17 is individually gain-adjusted to an upper limit value with respect to the valid data selected and set. The horizontal axis of FIG. 9 represents the wavelength, and the vertical axis represents the fluorescence signal intensity.

In step S404 for sample measurement, a single-stained sample for creating a reference spectrum, an unstained sample, and a multi-stained sample to be analyzed are measured with each channel of the PMT 17 individually adjusted to an upper limit. As a result of the measurement, as shown in FIG. 9, it is expected that most of each channel of the PMT 17 will be the upper limit of the measurement when the multi-staining sample is measured.

[Example of calculation of correction coefficient (S405)]
FIG. 10 is a diagram for explaining the calculation processing of the correction coefficient for the data including the data of the five fluorescent dyes of the spectral type flow cytometer 1. FIG. 10A shows a spectral shape in which all PMT17 channels are uniformly gain-adjusted to the upper limit of measurement. FIG. 10B shows the spectral shape of each PMT17 channel individually gain-adjusted to the upper limit of measurement. FIG. 10C shows the fluorescence spectrum shape obtained by multiplying the measured data shown in FIG. 10B by a correction coefficient. The horizontal axis of FIGS. 10A to 10C represents the wavelength, and the vertical axis represents the fluorescence signal intensity.

In step S405 for calculating the correction coefficient, the gain of each channel of the PMT 17 is adjusted to the upper limit of measurement, and the measured data is multiplied by the correction coefficient to reproduce the fluorescence spectrum shape. It can be seen that the corrected spectral shape shown in FIG. 10C can reproduce a spectral shape substantially equivalent to the spectral shape measured by uniformly adjusting all the channels of PMT17 shown in FIG. 10C. Further, from FIGS. 10A and 10B, in the channel measured by individually adjusting the gain of each PMT 17 to the upper limit of measurement, the measurement with less fixed noise is realized as compared with the case of uniformly adjusting the gain to the upper limit of measurement. It will be.

[Example of reference spectrum creation and unmixing processing (S406)]
FIG. 11 is a graph showing a reference spectrum calculated using the spectral type flow cytometer 1. FIG. 11A shows the calculated reference spectrum of the fluorescent dye BV 510, and FIG. 11B shows the calculated reference spectrum of Alexa Fluor 594. The horizontal axis of FIG. 11 represents the wavelength, and the vertical axis represents the normalized fluorescence signal intensity.

In step S406 for creating the reference spectrum, the average value and the like are calculated from the measured data of the corrected single-stained sample to calculate the reference spectrum. As shown in FIGS. 11A and 11B, the spectrum obtained by uniformly adjusting the gain of the PMT17 array (dotted line) and the spectrum obtained by individually adjusting and measuring the gain of the PMT17 array and applying the correction (solid line) are approximately the same. It turns out that they are the same. By taking the operation procedure of the fine particle measuring device of the present embodiment in this way, even if the gain of the PMT17 array is individually adjusted, it becomes possible to reproduce the spectral shape of the uniformly adjusted value, and the number of fluorescent dyes can be increased. The reference spectrum can be diverted even when the measurement is increased or decreased and the individual gain settings are different.

FIG. 12 is a calculation formula for performing fluorescence separation of the multiple staining sample using the reference spectrum. FIG. 12A shows a general least squares method (LSM) for Unmixing and FIG. 11B shows a general weighted least squares method (WLSM) for Unmixing.

In step S406 for performing the unmixing process, the multi-stained sample corrected in step S405 is subjected to the unmixing process (fluorescence separation) using the weighted least squares method (WLSM). Here, when LSM is used, data with a small signal is not so important, but when WLSM is used, the data of each channel of PMT17 is effectively used by weighting the signal size. Therefore, the influence of data with a small signal becomes large. However, for data that is too small, a parameter called Offset, which reflects the fixed noise of the device, is usually set to regulate its effect.

The present technology makes it possible to reduce and measure this fixed noise by individually optimizing the gain of each PMT17. Therefore, in the analysis of WLSM, by adjusting the Offset term according to the measurement data, higher fluorescence separation performance can be exhibited. Optimal analysis can be performed by simply multiplying the Offset term, which is usually uniform, by a coefficient corresponding to the correction coefficient used in the measurement data.

[Compatibility of individual gain settings and correction coefficient values]
With reference to FIGS. 13 and 14, the compatibility between the individual gain setting of the array type PMT17 and the value of the correction coefficient, which is one of the important elements of the present technology, will be described. Here, if the characteristics are in the initial state, the relationship between the applied voltage applied to the PMT 17 and the gain can be accurately estimated by evaluating the PMT 17 alone.

FIG. 13 is a graph showing an example of a characteristic curve based on the gain curve of PMT17. The horizontal axis of FIG. 13 represents the number of PMTs, and the vertical axis represents the gain. As shown in FIG. 13, since the characteristic curve of the present embodiment is not a monotonous curve and the gain changes rapidly, there is a concern about the influence of the characteristic change due to aged deterioration. Therefore, a procedure for re-evaluating the gain characteristics in the state where the PMT 17 is incorporated in the spectral type flow cytometer 1 is required. However, since the gain of PMT17 has a very wide range, if one minute particle is simply measured, the value is saturated or there is a region where it cannot be detected. Further, although it is possible to measure and calibrate fine particles whose brightness is changed stepwise multiple times, an error or the like occurs between measurements.

In order to solve this problem, as shown in FIG. 14, calibration is performed using a sample in which a plurality of fine particles having a broad fluorescence spectrum, different particle sizes, and different fluorescence intensities are mixed. FIG. 14A shows the spectral shapes of the samples to be mixed. The horizontal axis of FIG. 14A represents the wavelength, and the vertical axis represents the fluorescence signal intensity. FIG. 14B shows the measurement results of a sample in which a plurality of fine particles are mixed. The horizontal axis of FIG. 14B represents FSC (forward scattered light: forward scatter), and the vertical axis represents SSC (side scattered light side scatter). FIG. 14C shows the gain characteristics of the particles selected by the gate setting with respect to the measurement data shown in FIG. 14B. The horizontal axis of FIG. 14C represents the PMT applied voltage, and the vertical axis represents the fluorescence signal intensity.

As shown in FIG. 14C, in a normal flow cytometer, the forward scattered light is related to the particle size, and the particles can be selected by the gate setting separately from the fluorescence amount. By using this function, particles are identified from the measurement results of mixed particles, and the characteristics of the region with a large gain of PMT17 for small particles and the region with a small gain of PMT17 for large particles are evaluated, so that the measurement can be performed once and automatically. It is possible to calibrate the gain characteristics of the array type PMT17 over a wide range.

[Measurement of peak beads]
The measurement of the peak beads of the present embodiment will be described with reference to FIGS. 15 to 18. FIG. 15 is a diagram showing the measurement of 8-peak beads in which fine particles whose fluorescence intensity is adjusted in 8 steps for sensitivity evaluation are mixed. FIG. 15A shows a spectral shape in which all PMT17 channels are uniformly gain-adjusted to the upper limit of measurement. FIG. 15B shows the spectral shape of each PMT17 channel individually gain-adjusted to the upper limit of measurement. FIG. 15C shows the fluorescence spectrum shape obtained by multiplying the measured data shown in FIG. 15B by a correction coefficient. The horizontal axis of FIGS. 15A to 15C represents the wavelength, and the vertical axis represents the fluorescence signal intensity.

FIG. 16 is a diagram showing a spectral shape obtained by cutting out data for each fluorescence wavelength band of a typical fluorescent dye. The horizontal axis of FIG. 16 represents the wavelength, and the vertical axis represents the fluorescence signal intensity. FIG. 17 is a graph in which the gains of all PMT17 channels are uniformly adjusted to the upper limit of measurement and the separation performance of eight peaks is plotted. FIG. 18 is a graph in which the gain of each PMT17 channel is individually adjusted to the upper limit of measurement and the separation performance of eight peaks is plotted. The horizontal axis of FIGS. 17 and 18 represents the wavelength, and the vertical axis represents the number of particles.

As shown in FIG. 15, in order to confirm the fixed noise reduction effect when the gain of the PMT17 array is individually set, eight peak beads in which particles whose fluorescence intensity is adjusted in eight stages for sensitivity evaluation are mixed are mixed. Was measured. Then, as shown in FIGS. 16 to 18, data was cut out for each fluorescence wavelength band of a typical fluorescent dye, and the separation performance of eight peaks of the cut out data was plotted. As shown in FIGS. 17 and 18, there is almost no change in the separability of the PE region having high fluorescence intensity of the eight peak beads, but the other FITC region, PE-CY5 region, and PE-Cy7 region. It was found that the distinction between dark beads was clear in. At that time, since the average value of the fluorescence intensity of each bead is almost the same, it can be seen that the spectral shape is secured. From this result, it was confirmed that the operation procedure of the present technology could realize the measurement of reducing the fixed noise in each channel of the PMT17 having a small amount of fluorescence while ensuring the spectral shape.

As described above, the spectral type flow cytometer 1 of the present embodiment can measure under the condition that the fixed noise is small in all wavelength bands by optimizing the voltage of the PMT 17, and as a result, the separation ability of the fluorescent dye is improved. In addition, the spectral type flow cytometer 1 can increase the number of dyes that can be used at the same time by improving the separation ability of the proximity dyes.

Further, the spectral type flow cytometer 1 can reduce the burden of adjusting a large number of parameters by automatically calculating the voltage setting value of the PMT under the optimum conditions only by measuring the multi-staining sample.

Further, the spectrum type flow cytometer 1 can be used for analysis by using a correction coefficient in consideration of the gain of PMT17 for the measurement result, so that the reference spectrum used for fluorescence separation can be diverted. Then, even under different measurement conditions, the burden of measuring each single-stained sample can be reduced.

Further, the spectral type flow cytometer 1 can update the gain characteristic data while being incorporated in the apparatus simply by measuring the reference sample against the secular change of the gain characteristic of the PMT 17, and can always secure the optimum measurement conditions. ..

<3. Hardware configuration example>
Next, with reference to FIG. 19, the hardware configuration of the information processing apparatus according to the embodiment of the present disclosure will be described. FIG. 19 is a block diagram showing a hardware configuration example of the information processing apparatus according to the embodiment of the present disclosure. The illustrated information processing device 900 can realize, for example, the information processing device 10 according to the above embodiment.

The information processing device 900 includes a CPU (Central Processing Unit) 901, a ROM (Read Only Memory) 903, and a RAM (Random Access Memory) 905. Further, the information processing device 900 may include a host bus 907, a bridge 909, an external bus 911, an interface 913, an input device 915, an output device 917, a storage device 919, a drive 921, a connection port 925, and a communication device 929. The information processing apparatus 900 may have a processing circuit called a DSP (Digital Signal Processor) or an ASIC (Application Specific Integrated Circuit) in place of or in combination with the CPU 901.

The CPU 901 functions as an arithmetic processing device and a control device, and controls all or a part of the operation in the information processing device 900 according to various programs recorded in the ROM 903, the RAM 905, the storage device 919, or the removable recording medium 923. For example, the CPU 901 controls the overall operation of each functional unit included in the information processing apparatus 10 in the above embodiment. The ROM 903 stores programs, calculation parameters, and the like used by the CPU 901. The RAM 905 primarily stores a program used in the execution of the CPU 901, parameters that change appropriately in the execution, and the like. The CPU 901, ROM 903, and RAM 905 are connected to each other by a host bus 907 composed of an internal bus such as a CPU bus. Further, the host bus 907 is connected to an external bus 911 such as a PCI (Peripheral Component Interconnect / Interface) bus via a bridge 909.

The input device 915 is a device operated by the user, such as a mouse, a keyboard, a touch panel, buttons, switches, and levers. The input device 915 may be, for example, a remote control device using infrared rays or other radio waves, or an externally connected device 927 such as a mobile phone corresponding to the operation of the information processing device 900. The input device 915 includes an input control circuit that generates an input signal based on the information input by the user and outputs the input signal to the CPU 901. By operating the input device 915, the user inputs various data to the information processing device 900 and instructs the processing operation.

The output device 917 is composed of a device capable of visually or audibly notifying the user of the acquired information. The output device 917 can be, for example, a display device such as an LCD, PDP, or OELD, an acoustic output device such as a speaker and headphones, and a printer device. The output device 917 outputs the result obtained by the processing of the information processing device 900 as a video such as text or an image, or outputs as a sound such as sound.

The storage device 919 is a data storage device configured as an example of the storage unit of the information processing device 900. The storage device 919 is composed of, for example, a magnetic storage device such as an HDD (Hard Disk Drive), a semiconductor storage device, an optical storage device, an optical magnetic storage device, or the like. The storage device 919 stores programs executed by the CPU 901, various data, various data acquired from the outside, and the like. The storage device 919 can realize the function of the storage unit 110 according to the above embodiment.

The drive 921 is a reader / writer for a removable recording medium 923 such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, and is built in or externally attached to the information processing device 900. The drive 921 reads the information recorded on the mounted removable recording medium 923 and outputs the information to the RAM 905. Further, the drive 921 writes a record on the attached removable recording medium 923.

The connection port 925 is a port for directly connecting the device to the information processing device 900. The connection port 925 may be, for example, a USB (Universal Serial Bus) port, an IEEE1394 port, a SCSI (Small Computer System Interface) port, or the like. Further, the connection port 925 may be an RS-232C port, an optical audio terminal, an HDMI (registered trademark) (High-Definition Multimedia Interface) port, or the like. By connecting the externally connected device 927 to the connection port 925, various data can be exchanged between the information processing device 900 and the externally connected device 927.

The communication device 929 is, for example, a communication interface composed of a communication device for connecting to a communication network NW. The communication device 929 may be, for example, a communication card for a wired or wireless LAN (Local Area Network), Bluetooth (registered trademark), or WUSB (Wireless USB). Further, the communication device 929 may be a router for optical communication, a router for ADSL (Asymmetric Digital Subscriber Line), a modem for various communications, or the like. The communication device 929 transmits and receives signals and the like to and from the Internet and other communication devices using a predetermined protocol such as TCP / IP. The communication network NW connected to the communication device 929 is a network connected by wire or wirelessly, and is, for example, the Internet, a home LAN, infrared communication, radio wave communication, satellite communication, or the like.

It should be noted that each step in the processing of the information processing apparatus of the present specification does not necessarily have to be processed in chronological order in the order described as the flowchart. For example, each step in the processing of the information processing apparatus may be processed in an order different from the order described in the flowchart, or may be processed in parallel.

In addition, it is possible to create a computer program for causing hardware such as a CPU, ROM, and RAM built in the information processing device to exhibit the same functions as each configuration of the information processing device described above. A storage medium for storing the computer program is also provided.

In addition, the effects described herein are merely explanatory or exemplary and are not limited. That is, the techniques according to the present disclosure may exhibit other effects apparent to those skilled in the art from the description herein, in addition to or in place of the above effects.

Further, the embodiment according to the present technology is not limited to the above-described embodiment, and various changes can be made without departing from the gist of the present technology.

Further, the effects described in the present specification are merely examples and are not limited, and other effects may be obtained.

In addition, the present technology can have the following configurations.
(1)
A detector having a plurality of detectors for detecting light from fine particles,
A magnification setting unit that sets the magnification for each of the plurality of detectors,
A correction coefficient calculation unit that calculates the correction coefficient based on the set multiplication factor,
A spectrum generator that generates spectrum data by correcting the value detected by the detector with the calculated correction coefficient, and
A spectral type fine particle measuring device comprising.
(2)
The fine particle measuring device according to (1), further comprising an instrument control unit that individually adjusts the magnification of each of the plurality of detectors.
(3)
The fine particle measuring apparatus according to (1), further comprising a data adjusting unit that automatically adjusts the maximum value of the value detected by the detecting unit to a predetermined threshold value based on a set multiplication factor.
(4)
The fine particle measuring device according to (3), wherein the predetermined threshold value is a detection upper limit value of the detector.
(5)
The fine particle measuring apparatus according to (1), further comprising a reference spectrum calculation unit that calculates a reference spectrum based on the generated spectrum data.
(6)
The fine particle measuring apparatus according to (3), further comprising a spectrum separating unit for separating using a calculated reference spectrum.
(7)
The fine particle measuring apparatus according to (6), wherein the spectrum separation unit performs a spectrum separation process by using a weighted least squares method that weights based on the calculated correction coefficient.
(8)
The fine particle measuring device according to (1), wherein the magnification setting unit sets the magnification based on the applied voltage of the detector.
(9)
The fine particle measuring apparatus according to (1), wherein the correction coefficient is a value based on the uniformity of the detector, the width of the detected wavelength band for each of the plurality of detectors, or the wavelength dependence of photoelectric conversion.
(10)
The magnification setting unit automatically sets the magnification from one measurement data of a sample mixed with a single-stained sample stained with one fluorescent dye or a multi-stained sample stained with all fluorescent dyes (1). ). The fine particle measuring apparatus.
(11)
The correction coefficient calculation unit automatically calculates the correction coefficient from one measurement data of a sample mixed with a single-staining sample stained with one fluorescent dye or a multi-staining sample stained with all the fluorescent dyes (1). ). The fine particle measuring device.
(12)
The fine particle measuring apparatus according to (1), further comprising a detector evaluation unit that evaluates the detector using measurement data obtained by mixing a plurality of fine particles having different fluorescence intensities and particle diameters.
(13)
A magnification setting unit that sets the magnification for each of multiple detectors that detect light from fine particles,
A correction coefficient calculation unit that calculates the correction coefficient based on the set multiplication factor,
A spectrum generator that generates spectrum data by correcting the value detected by the detector with the calculated correction coefficient, and
Information processing device equipped with.
(14)
The processor,
Steps to set the magnification for each of multiple detectors that detect light from fine particles,
Steps to calculate the correction factor based on the set magnification and
A step of correcting the value detected by the detector with the calculated correction coefficient to generate spectrum data, and
Information processing methods including.

1 Flow cytometer 11 Laser light source 12 Lens 13 Fluid optical system 14 Filter detector 15 User interface 16 Prism 17 Array type high-sensitivity detector (PMT)
21 Fluorescent spectrum detection unit 22 Information processing device 23 Equipment control unit 24 Data recording unit 25 Data analysis unit 31 Multiplier setting unit 32 Correction coefficient calculation unit 33 Spectrum generation unit 34 Data adjustment unit 35 Reference spectrum calculation unit 36 Spectrum separation unit 37 Detection Instrument evaluation department

Claims (15)

A detector that detects light from dye-labeled microparticles and has multiple detectors with different detection wavelength bands.
A magnification setting unit that sets the magnification for each of the plurality of detectors,
A correction coefficient calculation unit that calculates the correction coefficient based on the set multiplication factor,
A spectrum generator that generates spectrum data by correcting the values detected by the plurality of detectors with the calculated correction coefficients, and
Equipped with a,
A spectral type fine particle measuring device in which the number of the plurality of detectors is larger than the number of the dyes. The fine particle measuring device according to claim 1, further comprising an instrument control unit that individually adjusts the magnification of each of the plurality of detectors. The fine particle measuring apparatus according to claim 1 or 2 , further comprising a data adjusting unit that automatically adjusts the maximum value of the value detected by the detecting unit to a predetermined threshold value based on a set multiplication factor. The fine particle measuring device according to claim 3, wherein the predetermined threshold value is a detection upper limit value of the detector. The microparticle measuring apparatus according to any one of claims 1 to 4, further comprising a reference spectrum calculation unit that calculates a reference spectrum based on the generated spectrum data. The fine particle measuring apparatus according to claim 3 or 4 , further comprising a spectrum separating unit for separating using a calculated reference spectrum. The fine particle measuring apparatus according to claim 6, wherein the spectrum separation unit performs spectrum separation processing by using a weighted least squares method that weights based on the calculated correction coefficient. The fine particle measuring device according to any one of claims 1 to 7, wherein the magnification setting unit sets the magnification based on the applied voltage of the detector. The minute amount according to any one of claims 1 to 8, wherein the correction coefficient is a value based on the uniformity of the detector, the width of the wavelength band detected for each of the plurality of detectors, or the wavelength dependence of photoelectric conversion. Particle measuring device. A claim that the magnification setting unit automatically sets the magnification from one measurement data of a sample mixed with a single-staining sample labeled with one fluorescent dye or a multi-staining sample labeled with all the fluorescent dyes. The microparticle measuring apparatus according to any one of 1 to 9. A claim that the correction coefficient calculation unit automatically calculates a correction coefficient from one measurement data of a sample mixed with a single-staining sample labeled with one fluorescent dye or a multi-staining sample labeled with all the fluorescent dyes. The microparticle measuring apparatus according to any one of 1 to 10. The fine particle measuring apparatus according to any one of claims 1 to 11, further comprising a detector evaluation unit that evaluates the detector using measurement data obtained by mixing a plurality of fine particles having different fluorescence intensities and particle diameters. Any of claims 1 to 12, further comprising a display unit for displaying the spectrum data. The fine particle measuring device according to item 1. A magnification setting unit that detects light from fine particles labeled with a dye and sets the magnification for each of a plurality of detectors having different detection wavelength bands.
A correction coefficient calculation unit that calculates the correction coefficient based on the set multiplication factor,
A spectrum generator that generates spectrum data by correcting the values detected by the plurality of detectors with the calculated correction coefficients, and
Equipped with a,
An information processing device in which the number of the plurality of detectors is larger than the number of the dyes. The processor,
A step of detecting light from fine particles labeled with a dye and setting a magnification for each of a plurality of detectors having different detection wavelength bands.
Steps to calculate the correction factor based on the set magnification and
A step of correcting the values detected by the plurality of detectors with the calculated correction coefficients to generate spectrum data, and
Only including,
An information processing method in which the number of the plurality of detectors is larger than the number of the dyes.

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